This research aims to identify genes that influence speech sound disorder (SSD) by applying a newly available approach to gene discovery, next-generation exome sequencing followed by bioinformatic gene filtering. Children with SSD have difficulty producing speech that is readily understood by others, in the absence of known causes. There is evidence that SSD is highly heritable, but the causal genes are not yet known. Recent studies in child sib pairs with SSD from many families have confirmed a number of candidate regions, but there is evidence that SSD can result from different genes in different families. To advance our knowledge, the common disease/rare variant (CDRV) model is an alternative framework for gene identification, using approaches that focus on only one genetic mechanism at a time. Recent insights from speech studies in adults who had SSD during childhood, coupled with an exome-based gene discovery approach, now make it possible to identify causal genes in single extended multigenerational families. The proposed research will identify up to two such families with evidence of single-gene inheritance of SSD, in addition to those already ascertained in a current pilot project. Phenotyping and statistical modeling will provide an estimate of the mode of inheritance of SSD and characterize associated traits in each family. Three distantly related, affected members will be selected for exome sequencing in each family. Exomic nucleotide sequences will be filtered to a core of candidate genes with novel nonsynonymous variants that are maximally shared by the sequenced exomes and fit the estimated mode of inheritance in terms of copy numbers. If more than one candidate gene per family remains, the one with the highest locus and/or functional plausibility will be selected for validation in affected and unaffected controls. This research has the realistic potential to identify single or major genes associated with SSD for the first time and provide the basis for future studies investigating other SSD variants and, by extension, other communication and neuro-developmental disorders with a CDRV pattern, all with substantially higher efficiency and lower cost than previously possible. Results will flow into a larger research endeavor to identify other rare variants in families with SSD and create a biologically based SSD subtype classification.